读者文摘:互联网时代如何保护隐私(7)（在线收听）

We all have secret “consumer scores,” hidden ratings that determine how long we wait on hold when calling a business,

我们都有秘密的“消费者评分”，隐藏的评级决定了我们在打电话给企业时等待的时间，

whether we can return items at a store, and what type of service we receive.

我们是否可以在商店退货，以及我们获得什么样的服务。

A low score sends you to the back of the queue; a high score gets you elite treatment.

一个低的评分会把你送到队列的后面；高分会让你得到精英待遇。

Little is known about these scores.

人们对这些分数知之甚少。

Most people have no inkling they even exist, and companies are mum about how they come up with them, or that they exist at all.

大多数人甚至对它们的存在一无所知，而公司对它们是如何产生的，或者它们的存在只字不提。

A watchdog group called the Consumer Education Foundation wants the Federal Trade Commission

一个叫做消费者教育基金会的监督组织想要联邦贸易委员会

to investigate secret surveillance scores “generated by a shadowy group of privacy-busting firms that operate in the dark recesses of the American marketplace.”

调查“由一群在美国市场的黑暗角落里运作的秘密破坏隐私的公司产生”的秘密监视得分。

The report named 11 firms that rate shoppers, potential renters, and prospective employees.

该报告列举了11家对购物者、潜在租户和潜在雇员进行评级的公司。

I got my file from one of these firms; others gave the runaround.

我从其中一家公司拿到了我的文件；其他人则在搪塞。

The company that cooperated, called Sift, says its “proprietary scoring system tracks consumer behavior with hundreds of companies.”

参与合作的公司名为希夫特，该公司称其“专有评分系统与数百家公司一起跟踪消费者行为。”

My report was shocking: More than 400 pages long, it contained all the messages I’d ever sent to hosts on Airbnb;

我的报告令人震惊：长达400多页，里面包含了我曾经发送给爱彼迎上的房东的所有信息；

years of Yelp delivery orders; a log of every time I’d opened the Coinbase app on my iPhone.

多年的Yelp外卖订单；记录我每次在苹果手机上打开Coinbase应用程序的日志。

Sift knew that I’d ordered chicken tikka masala on a Saturday night in April three years ago.

希夫特公司知道我在三年前4月的一个周六晚上点了咖喱鸡。

It knew about a nightmare Thanksgiving I had in California’s wine country, as captured in my messages to the Airbnb host of a rental called “Cloud 9.”

它知道我在加州的葡萄酒之乡度过了一场噩梦似的感恩节，这一点在我给爱彼迎上一个名为“云9”租赁服务的房东的信息中得到了体现。

The companies gathering the data say they find it valuable for rooting out fraud and increasing the revenue they can collect from big spenders.

收集数据的公司表示，他们发现这些数据对于根除欺诈行为和增加从大客户那里获得的收入很有价值。

But the process is far from transparent.

但这一过程远不透明。